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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 2-RES-JB
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    Explanations

    references to the city of Winnipeg

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the location Winnipeg and its context in various scenarios

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    arist
    -0.83
     bell
    -0.75
    egal
    -0.74
    asin
    -0.74
    å¦
    -0.73
    nces
    -0.72
    ential
    -0.72
    NEY
    -0.71
    abet
    -0.69
    Oracle
    -0.68
    POSITIVE LOGITS
    ipeg
    1.41
     Winnipeg
    1.26
     Manitoba
    1.15
     Jets
    0.98
     Springs
    0.96
     Saskatchewan
    0.95
    nown
    0.85
     Archdemon
    0.83
    atchewan
    0.80
     Moose
    0.80
    Activations Density 0.009%

    No Known Activations